Existing image comparison techniques often produce unreliable recognition results due to variations in lighting, scale and other factors such as errors in the normalization of the image being recognized. In addition, many existing techniques are computationally expensive. Consequently, existing techniques are difficult to realize on devices such as personal computers, mobile phones and cameras.
Additionally, media capturing, editing and viewing products often include options for users to annotate, categorize or otherwise organize images and videos within a digital media library. Users browse or search through their digital libraries according to these rubrics to view and upload media to the web. A user's success in finding a desired image or video they wish to experience or share is directly related to the quality in which their digital library was organized. Oftentimes, however, users do not have the time or the energy to organize their digital media library which negatively impacts their view of the product and ability to find desired media. Developers have had difficulty providing useful organization tools to users based on recognition of objects within a media collection.